The radiated noise of underwater targets apparently consists of non-Gaussian ingredients. In the paper, based on plenty of radiated noise data, non-Gaussian feature of target signals is studied via high-order cumulates. Then, from Bispectrum estimation and WALSH dimensionality reduction, 65 dimensional Bispectrum feature from different kind of targets is extracted. The results show that the approach can efficiently classify underwater targets, and the colored Gaussian noise is restrained. The ration of recognition can arrive 92% toward three different kinds of underwater targets.

Yuan Peng, Science and Technology on Underwater Test and Control Lab. (China)Lin Cao, Science and Technology on Underwater Test and Control Lab. (China)Lin Mu, Science and Technology on Underwater Test and Control Lab. (China)

Fengzhen Zhang, Science and Technology on Underwater Test and Control Lab. (China)Zhaohui Zhang, Science and Technology on Underwater Test and Control Lab. (China)